1. Field of the Invention
The present invention relates to an image processing system in which an image capture apparatus and an image processing apparatus are connected to each other via a network.
2. Description of the Related Art
Conventionally, there is known a technique for detecting an object in an image captured by an image capture apparatus such as a network camera by analyzing the image.
As an example of such a technique, there is a method of detecting whether a human body region or face region exists in an image. In this method, a feature amount such as a feature vector is detected from an input image, and comparison processing is performed using a recognition dictionary which holds the feature amount of a detection target object such as a human body or face. Then, a likelihood also called a similarity or evaluation value is detected as a result of the comparison processing, thereby detecting the detection target object. In this method, if the likelihood is greater than or equal to a predetermined threshold value, it is determined that the detection target object has been detected. If the detection target object is detected, it is possible to transmit the detected object to another apparatus on a network as a detection event, and the other apparatus can use the object.
As another example of a method of detecting an object in an image, there is known a method of expressing the positional relationship between local regions by a probability model, and recognizing a human face or vehicle by learning (e.g., see “The Current State and Future Forecast of General Object Recognition”, Journal of Information Processing: The Computer Vision and Image Media, Vol. 48, No. SIG16 (CVIM19)).
It has been also proposed to apply a technique for detecting an object from an image to a system such as a monitoring apparatus. There has been proposed, for example, a technique for transmitting detected event information to a monitoring apparatus via a network together with an image upon detecting an object (see, for example, Japanese Patent Laid-Open No. 7-288802).
Furthermore, there has been conventionally proposed a technique for executing detection processing on the terminal side in accordance with the stop/non-stop state of mobile object detection in a camera (see, for example, Japanese Patent Laid-Open No. 2008-187328).
There is conventionally known a distributed image processing apparatus which has the first image processing apparatus for performing processing using a captured image and the second image processing apparatus for performing detailed processing for a stored image based on an index created by the first image processing apparatus. In this distributed image processing apparatus, the first image processing apparatus creates an index such as an intrusion object detection result or vehicle number recognition processing result. The second image processing apparatus extracts the feature amount of an image for only an image frame to undergo the detailed processing (e.g., see Japanese Patent Laid-Open No. 2007-233495).
Unlike a general-purpose personal computer or server, however, the throughput of a camera is low due to general restrictions on hardware resources such as a CPU and memory. It may be difficult to perform real time processing when a low-throughput camera performs a detection operation with a high processing load such as a human body detection operation, or processes a high-resolution image. Furthermore, in a detection method in which comparison is made using a recognition dictionary, such as pattern recognition, a detection operation may not be performed with high accuracy due to a limited capacity of the recognition dictionary of detection target objects.
On the other hand, assume that a server such as an image processing server receives a captured image or its metadata from a camera to execute detection processing. In this case, if the number of connected cameras increases, the server may no longer be able to handle the processing since the load is concentrated on it.